scholarly journals E-Learning Scenarios Using Intelligent Multiagent Systems

2015 ◽  
Author(s):  
Ali M. Aseere
Keyword(s):  
Multiagent Systems ◽  
E Learning ◽  
Learning Scenarios

scholarly journals The Usefulness of Video Learning Analytics in Small Scale E-Learning Scenarios

2021 ◽  
Vol 11 (21) ◽  
pp. 10366
Author(s):  
César Córcoles ◽  
Germán Cobo ◽  
Ana-Elena Guerrero-Roldán
Keyword(s):  
Learning Process ◽  
Teaching And Learning ◽  
Large Scale ◽  
Real Data ◽  
Small Scale ◽  
E Learning ◽  
Learning Scenarios ◽  
Real Scenario ◽  
Teaching Learning ◽  
Learning Data

A variety of tools are available to collect, process and analyse learning data obtained from the clickstream generated by students watching learning resources in video format. There is also some literature on the uses of such data in order to better understand and improve the teaching-learning process. Most of the literature focuses on large scale learning scenarios, such as MOOCs, where videos are watched hundreds or thousands of times. We have developed a solution to collect clickstream analytics data applicable to smaller scenarios, much more common in primary, secondary and higher education, where videos are watched tens or hundreds of times, and to analyse whether the solution is useful to teachers to improve the learning process. We have deployed it in a real scenario and collected real data. Furthermore, we have processed and presented the data visually to teachers for those scenarios and have collected and analysed their perception of their usefulness. We conclude that the collected data are perceived as useful by teachers to improve the teaching and learning process.

Individual and Socio-Cultural Framing of E-Learning

2014 ◽  
pp. 1-20
Author(s):  
Bernhard Ertl ◽  
Kathrin Helling
Keyword(s):  
Knowledge Construction ◽  
Learning Processes ◽  
Cultural Perspective ◽  
Cultural Contexts ◽  
Design And Implementation ◽  
E Learning ◽  
Learning Scenarios ◽  
The Individual ◽  
Collaborative Knowledge ◽  
Collaborative Knowledge Construction

Considering e-learning as a socio-cultural system acknowledges that individuals are embedded within different contexts, influenced by the culture and the society the individual lives in. Designing beneficial e-learning scenarios means respecting these socio-cultural contexts and providing appropriate framing. This chapter introduces several aspects influencing e-learning from an individual and socio-cultural perspective. It firstly deals with the aspect of learners' collaborative knowledge construction in e-learning and introduces what this perspective means for the design and implementation of e-learning scenarios. The chapter looks at tools and shared external representations and shows how they can beneficially support learning processes and outcomes. In a third step, it looks at the individual's learning characteristics, for example an individual's prior knowledge, and socio-cultural biases relating to gender, ethnicity, and socio economic background, and discusses how these may be an obstacle for e-learning and how e-learning may help learners to overcome their biases. Finally, the chapter focuses on the issue on evaluation and provides suggestions to evaluate environments for e-learning from a socio-cultural perspective.

Infallibility of Innovative Artefacts

2010 ◽  
pp. 86-106
Author(s):  
Karim A. Remtulla
Keyword(s):  
Adult Learning ◽  
Technological Innovation ◽  
Learning Objects ◽  
Cultural Impacts ◽  
Cultural Paradigm ◽  
E Learning ◽  
Learning Scenarios ◽  
Learning Research ◽  
Similarities And Differences ◽  
And Training

This chapter discusses the cultural paradigm of ‘innovative artefacts’ in the workplace. This cultural paradigm is one of two proposed paradigms that shape socio-culturally insensitive, technological artefactual approaches to workplace e-learning research and study. Subsequently, this paradigm also socially reshapes workplace e-leaning historicity for workplace adult education and training, resulting in socio-cultural impacts on the workforce. Technological innovation and business process change dominate workplace transformations. At the same time, any discussion on the socio-cultural impacts of workplace e-learning must also take into account that workplace e-learning is arguably both a technological innovation and as well as a business administration process, all of which affect adult learning in the workplace. Critical theory problematizes these relations between technology and technological progress as well as workplace e-learning. The ‘presumption of neutrality’ is highlighted as it influences the shaping of workplace e-learning and its dubious, shifting, and reversible impacts on the workforce. A focused discourse analysis of the connotations and assumptions that have further shaped e-learning for the workplace over the past decade illustrate workplace e-learning’s changing emphases over the years, from administrational to associational to artefactual, today. The technological artefacts of workplace elearning now deserve closer scrutiny. The similarities and differences between ‘online learning and simulations’, ‘learning objects’, and ‘learning management systems’ are highlighted as each of these technological artefacts, more often than not, is taken as equivalent to and a substitute for learning. The ‘presumption of neutrality’ now also comes to fruition in the ‘infallibility paradox’ for workplace e-learning. For workplace e-learning, adherence to the belief in the infallibility of innovative artefacts leads to two workplace e-learning scenarios: (a) instrumental instruction (see Chapter 7); and, (b) rational training (see Chapter 8).

Redressing Socio-Cultural Insensitivity

2010 ◽  
pp. 66-85
Author(s):  
Karim A. Remtulla
Keyword(s):  
Adult Education ◽  
Social Theory ◽  
Cultural Sensitivity ◽  
Common Ground ◽  
Global Workforce ◽  
Diverse Field ◽  
Culturally Based ◽  
E Learning ◽  
Learning Scenarios ◽  
Learning Research

This chapter concerns many of the challenges facing socio-cultural researchers of workplace e-learning when attempting a social critique of workplace elearning. These obstacles include finding a common ground to begin a socio-culturally based research and study of workplace e-learning as well as using an approach that authentically balances ‘distance’ and ‘education’ so that distance education does not become a ‘distant education’. The overwhelming emphasis on the technological artefacts of workplace e-learning are not having the expected impacts on workplace adult education and training to the degree so profoundly anticipated by so many. The research and study of workplace e-learning as a socio-culturally negotiated ‘idea’ may be one such way. To do this, notions of social theory, taxonomy, and the researcher, as they relate to the field of adult education, and for a global workforce of adult learners, now become necessary. The complexity of approaching the diverse field of adult education with respect to social theory is explained, as are some of the challenges of applying the socio-cultural sensitivity taxonomy by using adult education as a backdrop for understanding workplace e-learning. ‘Socio-cultural Sensitivity Taxonomy for Workplace E-learning’ is presented and comprises four basic elements: (a) a context (social change) and an impetus (social responsibility) for a socio-culturally based research and study of workplace e-learning; (b) two outcomes (normalization and universalization) of technological artefactual approaches to workplace e-learning research and study; (c) two dominant cultural paradigms (commodified knowledges and innovative artefact) shaping workplace e-learning historicity in organizations; and, (d) four workplace e-learning scenarios (instrumental instruction, rational training, dehumanizing ideologies, and social integration), that all present socio-cultural impacts for the workforce from socio-culturally insensitive, technological artefactual approaches to workplace e-learning research and study. Figure 1 and Figure 2, originally from the Preface, are re-presented here, more formally.

The Potential of IMS Learning Design in E-Learning

2011 ◽  
pp. 65-78
Author(s):  
Diana M. Ragbir ◽  
Permanand Mohan
Keyword(s):  
Learning Process ◽  
Learning Objects ◽  
Learning Design ◽  
Design Specification ◽  
Instructional Needs ◽  
E Learning ◽  
Learning Scenarios ◽  
Actual Learning

This chapter presents the IMS Learning Design Specification and explains how it can be used to enhance the effectiveness of e-Learning scenarios. It shows how to assemble a learning design using elements of the learning process and chunks of content known as learning objects. The chapter proposes several learning design services that can potentially improve the pedagogical expressiveness of the current Learning Design Specification. It also discusses the possibility of storing learning designs in a repository and adapting and personalizing learning designs according to the instructional needs of individual learners. It is hoped that researchers and practitioners will understand how it is possible to go beyond learning objects and create learning designs that more accurately reflect the actual learning process of students and thus appreciate the value in extending the learning design specification to improve pedagogical effectiveness.

Goal-Based Framework for Multi-User Personalized Similarities in e-Learning Scenarios

2014 ◽  
Vol 4 (1) ◽  
pp. 1-14 ◽  
Author(s):  
M. Waseem Chughtai ◽  
Imran Ghani ◽  
Ali Selamat ◽  
Seung Ryul Jeong
Keyword(s):  
Collaborative Filtering ◽  
Cold Start ◽  
Traditional Education ◽  
Experimental Result ◽  
Personalized Recommendation ◽  
Web Based ◽  
Web Based Learning ◽  
E Learning ◽  
Learning Scenarios ◽  
Content Based Filtering

Web-based learning or e-Learning in contrast to traditional education systems offer a lot of benefits. This article presents the Goal-based Framework for providing personalized similarities between multi users profile preferences in formal e-Learning scenarios. It consists of two main approaches: content-based filtering and collaborative filtering. Because only traditional content-based filtering is not sufficient to generate the recommendations for new-users, therefore, the proposed work hybridized multi user's collaborative filtering functionalities with personalized content-based profile preferences filtering. The main purpose of this proposed work is to (a) overcome the user-based cold-start profile recommendations and (b) improve the recommendations accuracy for new-users in formal e-learning recommendation systems. The experimental has been done by using the famous ‘MovieLens' dataset with 15.86% density of the user-item matrix with respect to ratings, while the evaluation of experimental results have been performed with precision mean and recall mean to test the effectiveness of Goal-based personalized recommendation framework. The Experimental result Precision: 81.90% and Recall: 86.56% show that the proposed framework goals performed well for the improvement of user-based cold-start issue as well as for content-based profile recommendations, using multi users personalized collaborative similarities, in formal e-Learning scenarios effectively.

scholarly journals Adaptive Learning Recommendation Strategy Based on Deep Q-learning

2019 ◽  
Vol 44 (4) ◽  
pp. 251-266 ◽  
Author(s):  
Chunxi Tan ◽  
Ruijian Han ◽  
Rougang Ye ◽  
Kani Chen
Keyword(s):  
Adaptive Learning ◽  
Recommendation System ◽  
Personalized Recommendation ◽  
Early Stopping ◽  
Q Learning ◽  
E Learning ◽  
Learning Scenarios ◽  
Efficient Learning ◽  
Recommendation Strategy ◽  
Full Utilization

Personalized recommendation system has been widely adopted in E-learning field that is adaptive to each learner’s own learning pace. With full utilization of learning behavior data, psychometric assessment models keep track of the learner’s proficiency on knowledge points, and then, the well-designed recommendation strategy selects a sequence of actions to meet the objective of maximizing learner’s learning efficiency. This article proposes a novel adaptive recommendation strategy under the framework of reinforcement learning. The proposed strategy is realized by the deep Q-learning algorithms, which are the techniques that contributed to the success of AlphaGo Zero to achieve the super-human level in playing the game of go. The proposed algorithm incorporates an early stopping to account for the possibility that learners may choose to stop learning. It can properly deal with missing data and can handle more individual-specific features for better recommendations. The recommendation strategy guides individual learners with efficient learning paths that vary from person to person. The authors showcase concrete examples with numeric analysis of substantive learning scenarios to further demonstrate the power of the proposed method.

scholarly journals 3D Interactions between Virtual Worlds and Real Life in an E-Learning Community

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Ulrike Lucke ◽  
Raphael Zender
Keyword(s):  
Learning Community ◽  
Virtual Worlds ◽  
Real World ◽  
Second Life ◽  
Virtual World ◽  
Real Life ◽  
Face To Face ◽  
Learning Platform ◽  
E Learning ◽  
Learning Scenarios

Virtual worlds became an appealing and fascinating component of today's internet. In particular, the number of educational providers that see a potential for E-Learning in such new platforms increases. Unfortunately, most of the environments and processes implemented up to now do not exceed a virtual modelling of real-world scenarios. In particular, this paper shows that Second Life can be more than just another learning platform. A flexible and bidirectional link between the reality and the virtual world enables synchronous and seamless interaction between users and devices across both worlds. The primary advantages of this interconnection are a spatial extension of face-to-face and online learning scenarios and a closer relationship between virtual learners and the real world.

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